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| Information Retrieval | 5 |
| Relevance (Information… | 5 |
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| Deogun, Jitender S. | 1 |
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| Guglielmo, Eugene J. | 1 |
| Holmes, David O. | 1 |
| Lundquist, Carol | 1 |
| Morrissey, J. M. | 1 |
| Raghavan, Vijay V. | 1 |
| Rowe, Neil C. | 1 |
| Wisniewski, Janusz L. | 1 |
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Peer reviewedRowe, Neil C.; Guglielmo, Eugene J. – Information Processing and Management, 1993
Discusses the use of natural language processing to help organize multimedia data. The MARIE system, which uses captions to embody the classificatory information and heuristic advice necessary to search a database of photographs, is explained. Advantages include improved speed of access and the ability for improved user interaction. (Contains 21…
Descriptors: Access to Information, Captions, Database Design, Database Management Systems
Peer reviewedWisniewski, Janusz L. – Information Processing and Management, 1986
Discussion of a new method of index term dictionary compression in an inverted-file-oriented database highlights a technique of word coding, which generates short fixed-length codes obtained from the index terms themselves by analysis of monogram and bigram statistical distributions. Substantial savings in communication channel utilization are…
Descriptors: Algorithms, Database Management Systems, Databases, Information Retrieval
Peer reviewedLundquist, Carol; Frieder, Ophir; Holmes, David O.; Grossman, David – Journal of the American Society for Information Science, 1999
Describes a scalable, parallel, relational database-drive information retrieval engine. To support portability across a wide range of execution environments, all algorithms adhere to the SQL-92 standard. By incorporating relevance feedback algorithms, accuracy is enhanced over prior database-driven information retrieval efforts. Presents…
Descriptors: Database Design, Database Management Systems, Feedback, Information Management
Peer reviewedMorrissey, J. M.; And Others – Information Processing and Management, 1986
Proposes a "Model of Querying" for users of office filing facilities and discusses its motivation, aspects, attributes, and advantages. A review of current information systems and attempts to combine information retrieval, artificial intelligence, and database management techniques leads to conclusion that no resultant system is adequate…
Descriptors: Artificial Intelligence, Comparative Analysis, Database Management Systems, Databases
Peer reviewedDeogun, Jitender S.; Raghavan, Vijay V. – Information Processing and Management, 1988
Discusses the motivation for integrating information retrieval and database management systems, and proposes a probabilistic retrieval model in which records in a file may be composed of attributes (formatted data items) and descriptors (content indicators). The details and resolutions of difficulties involved in integrating such systems are…
Descriptors: Database Management Systems, Feedback, Information Retrieval, Mathematical Models


